Our question generator \(P_q(\mathbf {q}_i \mid D, i, a_i)\)  takes in the answer sentence \(\mathbf {s}_i\)  indexed by \(i\) , the anchor sentence at \(a_i\) , and the article \(D\) , and aims to generate an appropriate QUD.
We fine-tune GPT-2 [1]} for this purpose; [2]} showed that GPT-2 generates open-ended, high-level questions with good quality.
To fine-tune this model, each input instance is a concatenation of four parts, separated by delimiters: (1) \(\mathbf {s}_0,\mathbf {s}_1,...,\mathbf {s}_{i-1}\) ,
with the start and end of the anchor sentence marked by special tokens; (2) the anchor sentence; (3) \(\mathbf {s}_i\) ; (4) the question.
